Context-Dependent Cell Population Dynamics

NEW DRAQ7 ARTICLE: Investigation of complex cell population dynamics

Garvey et al. (Scientific Reports 6:29752; Published 25th July, 2016; Open access) from USC, UMN & Stanford describe a high-content imaging approach to monitoring heterogeneous cell population dynamics in the context of time and different possibly co-occurring selective pressures such as therapy, hypoxia, microenvironment and so on. For example, they were able to differentiate between cytostatic and cytotoxic effects of anti-cancer compounds on cell mixtures with different sensitivities that would have been masked by bulk measurements of MTS, ATP or total cell numbers. They demonstrate their approach in both 2-D and 3-D culture systems and suggest it would be amenable to any lab with a live-cell imaging platform (not only HCS equipment), utilising open-source software or proprietary alternatives. What they propose is a synthesis of mostly pre-existing techniques reminding us of the complexity of the systems we are trying to mimic in in vitro cancer cell biology!

In some examples they combine Hoechst 33342 (all nucleated cells) and DRAQ7 (dead/leaky cells) to monitor cell population death, stasis and expansion for 2-D culture and 3-D spheroids composed of two isogenically-identical cell types differing only in their sensitivity to chemotherapy and marked accordingly by constitutive GFP and RFP expression.

To show the limitations of detachment of adherent cells for analysis by flow cytometry they used the same reagent combination.

The far-red viability probe DRAQ7 demonstrates its cross-platform capabilities and amenability to HCS methodologies.  Though not exploited here, DRAQ7 can also be applied in the culture medium to enable monitoring in time-lapse mode. A white paper on this is available here:
http://tinyurl.com/z7vp5sy

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Reference:
Garvey, C.M., Spiller, E., Lindsay, D., Chiang, C.T., Choi, N.C., Agus, D.B., Mallick, P., Foo, J. and Mumenthaler, S.M., 2016. A high-content image-based method for quantitatively studying context-dependent cell population dynamics. Scientific Reports, 6, p.29752.